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Varvara68 [4.7K]
3 years ago
9

Randy presses RAND on his calculator twice to obtain two random numbers between 0 and 1. Let $p$ be the probability that these t

wo numbers and 1 form the sides of an obtuse triangle. Find $4p$.
Mathematics
2 answers:
Ludmilka [50]3 years ago
7 0

Answer:

pi - 2 would be the answer to AoPs.

anygoal [31]3 years ago
6 0

Answer:

\frac{\pi}{4}

Step-by-step explanation:

Lets call x,y the numbers we obtain from the calculator. x and y are independent random variables of uniform[0,1] distribution.

Lets note that, since both x and y are between 0 and 1, then 1 is the biggest side of the triangle.

Lets first make a geometric interpretation. If the triangle were to be rectangle, then the side of lenght 1 should be its hypotenuse, and therefore x and y should satisfy this property:

x²+y² = 1

Remember that in this case we are supposing the triangle to be rectangle. But the exercise asks us to obtain an obtuse triangle. For that we will need to increase the angle obtained by the sides of lenght x and y. We can do that by 'expanding' the triangle, but if we do that preserving the values of x and y, then the side of lenght 1 should increase its lenght, which we dont want to. Thus, if we expand the triangle then we should also reduce the value of x and/or y so that the side of lenght 1 could preserve its lenght. With this intuition we could deduce that

x²+y² < 1

Now lets do a more mathematical approach. According to the Cosine theorem, a triangle of three sides of lenght a,b,c satisfies

a² = b²+c² - 2bc* cos(α), where α is the angle between the sides of lenght b and c.

Aplying this formula to our triangle, we have that

1^2 = x^2 + y^2 - 2bc* cos(\alpha) , where \alpha is the angle between the sides of lenght x and y.

Since the triangle is obtuse, then \pi/2 <  \alpha < \pi , and for those values cos(\alpha) is negative , hence we also obtain

1 > x² + y²

Thus, we need to calculate P(x²+y² <1). This probability can be calculated throught integration. We need to use polar coordinates.

(x, y) = (r*cosФ,r*senФ)

Where r is between 0 and 1, and Ф is between 0 and \pi /2 (that way, the numbers are positive).

The jacobian matrix has determinant r, therefore,

{\int\int}\limits_{x^2+y^2 < 1}  \, dxdy = \int\limits^1_0\int\limits^{\frac{\pi}{2}}_0 {r} \, d\phi dr = \frac{\pi}{2} * \int\limits^1_0 {r} \, dr =    \frac{\pi}{2} * (\frac{r^2}{2} |^1_0) = \frac{\pi}{4}

As a conclusion, the probability of obtaining an obtuse triangle is \frac{\pi}{4} .

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Each front tire on a particular type of vehicle is supposed to be filled to a pressure of 26 psi. Suppose the actual air pressur
Ostrovityanka [42]

Answer:

1) K = 7.895 × 10⁻⁶

2) 0.3024

3)  3.6775 × 10⁻²

4) f(x)= \frac{1}{20} +\frac{3x^{2} }{38000}

5) X and Y are not independent variables

6)

h(x\mid y)  = \frac{38000x^2+38000y^2}{3y^2+19000}

7)  0.54967

8)  25.33 psi

σ = 2.875

Step-by-step explanation:

1) Here we have

f(x, y) =\begin{cases} & \text (x^{2}+y^{2}) \right. 20\leq x\leq 30 & \ 0 \, Otherwise\end{cases}

\int_{x}\int_{y} f(x, y)dydx = 1    

\int_{x}( \right )\int_{y} f(x, y)dy)dx = 1

K\int_{x}( \right )\int_{y}(x^{2} +y^{2})dy)dx = 1

K\int_{x}( (x^{2}y +\frac{y^{3}}{3})_{20}^{30})dx = 1

K\int_{x}( (x^{2}(30-20)) +\frac{30^{3}-20^{3}}{3})_{20}^{30})dx = 1

K\int_{x}( (10x^{2})+\frac{19000}{3})_{20}^{30})dx = 1

K( (10\frac{x^{3}}{3})+\frac{19000}{3}x)_{20}^{30})= 1

K( (10\frac{30^{3}-20^{3}}{3})+\frac{19000}{3}(30-20)))_{20}^{30}) = 1

K =\frac{3}{380000}

2) The probability that both tires are underfilled

P(X≤26,Y≤26) =

\int_{20}^{26} \int_{20}^{26}K(x^{2}+y^{2})dydx

=K\int_{x}( \right )\int_{y}(x^{2} +y^{2})dy)dx

= K\int_{x}( (x^{2}y +\frac{y^{3}}{3})_{20}^{26})dx

K\int_{x}( (x^{2}(26-20)) +\frac{26^{3}-20^{3}}{3})_{20}^{26})dx

K\int_{x}( (6x^{2})+\frac{9576}{3})_{20}^{26})dx

K( (6\frac{x^{3}}{3})+\frac{9576}{3}x)_{20}^{26})

K( (6\frac{26^{3}-20^{3}}{3})+\frac{9576}{3}(26-20)))_{20}^{26})

38304\times K =\frac{3\times38304}{380000}

= 0.3024

That is P(X≤26,Y≤26) = 0.3024

3) The probability that the difference in air pressure between the two tires is at most 2 psi is given by

{20 ≤ x ≤ 30, 20 ≤ y ≤ 30, |  x-y | ≤ 2}

{20 ≤ x ≤ 30, 20 ≤ y ≤ 30, \sqrt{(x-y)^2} ≤ 2}

{20 ≤ x ≤ 30, 20 ≤ y ≤ 30, y ≤ x - 2}

Which gives

20 ≤ x ≤ 22 ::      20 ≤ y ≤ x + 2

22 ≤ x ≤ 28 ::      x - 2 ≤ y ≤ x + 2

28 ≤ x ≤ 30 ::      x - 2 ≤ y ≤ 30

From which we derive probability as

P( |  x-y | ≤2) =  \int_{28}^{30} \int_{x-2}^{30}K(x^{2}+y^{2})dydx +  \int_{20}^{22} \int_{20}^{x+2}K(x^{2}+y^{2})dydx +  \int_{22}^{28} \int_{x-2}^{x+2}K(x^{2}+y^{2})dydx

= K (  \int_{28}^{30} \int_{x-2}^{30}K(x^{2}+y^{2})dydx +  \int_{20}^{22} \int_{20}^{x+2}K(x^{2}+y^{2})dydx +  \int_{22}^{28} \int_{x-2}^{x+2}K(x^{2}+y^{2})dydx)

= K\left [ \left (\frac{14804}{15}  \right )+\left (\frac{8204}{15}  \right ) +\left (\frac{46864}{15}  \right )\right ] = \frac{3}{380000}\times \frac{69872}{15} =\frac{4367}{118750} = 3.6775 × 10⁻²

4) The marginal pressure distribution in the right tire is

f_{x}\left ( x \right )=\int_{y} f(x ,y)dy

=K( \right )\int_{y}(x^{2} +y^{2})dy)

= K( (x^{2}y +\frac{y^{3}}{3})_{20}^{30})

K( (x^{2}(30-20)) +\frac{30^{3}-20^{3}}{3})_{20}^{30})

K(10x^{2}+\frac{19000}{3})}

\frac{3}{38000} (10x^{2}+\frac{19000}{3})}

= \frac{1}{20} +\frac{3x^{2} }{38000}

f(x)= \frac{1}{20} +\frac{3x^{2} }{38000}

5) Here we have

The product of marginal distribution given by

f_x(x) f_y(y) = ( \frac{1}{20} +\frac{3x^{2} }{38000})( \frac{1}{20} +\frac{3y^{2} }{38000}) =\frac{(3x^2+1900)(3y^2+1900)}{1444000000}

≠ f(x,y)

X and Y are not independent variables since the product of the marginal distribution is not joint probability distribution function.

6) Here we have the conditional probability of Y given X = x and the conditional probability of X given that Y = y is given by

h(y\mid x) =\frac{f(x,y))}{f_{X}\left (x  \right )}=  Here we have

 

h(y\mid x) =\frac{x^2+y^2}{\frac{1}{20} +\frac{3x^2}{38000} } = \frac{38000x^2+38000y^2}{3x^2+19000}

Similarly, the the conditional probability of X given that Y = y is given by

h(x\mid y) =\frac{x^2+y^2}{\frac{1}{20} +\frac{3y^2}{38000} } = \frac{38000x^2+38000y^2}{3y^2+19000}

7) Here we have

When the pressure in the left tire is at least 25 psi gives

K\int\limits^{25}_{20}  \frac{38000x^2+38000y^2}{3x^2+19000} {} \, dx

Since x = 22 psi, we have

K\int\limits^{25}_{20}  \frac{38000\cdot 25^2+38000y^2}{3\cdot 25^2+19000} {} \, dx = K \int\limits^{25}_{20}  10.066y^2+6291.39, dx = 57041.942\times \frac{3}{380000}= 0.45033

For P(Y≥25) we have

K \int\limits^{30}_{25}  10.066y^2+6291.39, dx = 69624.72\times \frac{3}{380000} = 0.54967

8) The expected pressure is the conditional mean given by

E(Y\mid x) = K\int\limits^{30}_{20} yh(y \mid x)\, dy

E(Y\mid x) = K\int\limits^{30}_{20} 10.066y^3+6291.39y\, dy = \frac{3}{380000} \times 3208609.27153

= 25.33 psi

The standard deviation is given by

Standard \, deviation =\sqrt{Variance}

Variance = K\int\limits^{30}_{20} [y-E(Y\mid x) ]^2h(y \mid x)\, dy

=K\int\limits^{30}_{20} [y-25.33]^2(10.066y^2+6291.39)\, dy

= \frac{3}{380000} \times 1047259.78 = 8.268

The standard deviation = √8.268 = 2.875.

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